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Open Access Research article

"Sleep disparity" in the population: poor sleep quality is strongly associated with poverty and ethnicity

Nirav P Patel1, Michael A Grandner23*, Dawei Xie4, Charles C Branas4 and Nalaka Gooneratne235

Author Affiliations

1 Respiratory Specialists and Reading Hospital and Medical Center, Reading, PA, USA

2 Center for Sleep and Respiratory Neurobiology, University of Pennsylvania, Philadelphia, PA, USA

3 Division of Sleep Medicine, Department of Medicine, University of Pennsylvania, Philadelphia, PA, USA

4 Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA, USA

5 Division of Geriatric Medicine, Department of Medicine, University of Pennsylvania, Philadelphia, PA, USA

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BMC Public Health 2010, 10:475  doi:10.1186/1471-2458-10-475

Published: 11 August 2010

Abstract

Background

Little is known about the social determinants of sleep attainment. This study examines the relationship of race/ethnicity, socio-economic status (SES) and other factors upon sleep quality.

Methods

A cross-sectional survey of 9,714 randomly selected subjects was used to explore sleep quality obtained by self-report, in relation to socioeconomic factors including poverty, employment status, and education level. The primary outcome was poor sleep quality. Data were collected by the Philadelphia Health Management Corporation.

Results

Significant differences were observed in the outcome for race/ethnicity (African-American and Latino versus White: unadjusted OR = 1.59, 95% CI 1.24-2.05 and OR = 1.65, 95% CI 1.37-1.98, respectively) and income (below poverty threshold, unadjusted OR = 2.84, 95%CI 2.41-3.35). In multivariable modeling, health indicators significantly influenced sleep quality most prominently in poor individuals. After adjusting for socioeconomic factors (education, employment) and health indicators, the association of income and poor sleep quality diminished, but still persisted in poor Whites while it was no longer significant in poor African-Americans (adjusted OR = 1.95, 95% CI 1.47-2.58 versus OR = 1.16, 95% CI 0.87-1.54, respectively). Post-college education (adjusted OR = 0.47, 95% CI 0.31-0.71) protected against poor sleep.

Conclusions

A "sleep disparity" exists in the study population: poor sleep quality is strongly associated with poverty and race. Factors such as employment, education and health status, amongst others, significantly mediated this effect only in poor subjects, suggesting a differential vulnerability to these factors in poor relative to non-poor individuals in the context of sleep quality. Consideration of this could help optimize targeted interventions in certain groups and subsequently reduce the adverse societal effects of poor sleep.